Cloud Developer - MLOps

Job description

Key Responsibilities

Cloud Infrastructure: Design, develop, and maintain robust AWS cloud infrastructure to support large-scale applications. Architect and implement scalable solutions using AWS services such as EC2, S3, Lambda, RDS, IAM, VPC, CloudFormation, and more.

MLOps

Implement and manage MLOps pipelines to streamline the deployment and monitoring of machine learning models. Automate model training, validation, deployment, and monitoring processes to ensure efficiency and reliability.

Large Language Models (LLM)

Utilize expertise in LLM to enhance our AI-driven solutions, including fine-tuning and optimizing pre-trained models.

DevOps Capabilities

Develop and maintain CI/CD pipelines using tools such as Jenkins, GitLab CI, CircleCI, or AWS CodePipeline. Implement infrastructure as code (IaC) practices using Terraform, CloudFormation, or AWS CDK. Ensure the highest levels of security, scalability, and performance in all cloud deployments. Monitor and manage the health, performance, and security of cloud environments using AWS CloudWatch, ELK stack (Elasticsearch, Logstash, Kibana), or Prometheus & Grafana.

Collaboration & Mentorship

Collaborate closely with data scientists, engineers, and stakeholders to drive innovation and optimize cloud-based solutions. Mentor and guide junior engineers, fostering a culture of continuous learning and improvement.

Technical Expertise & Innovation

Stay up-to-date with the latest advancements in cloud technologies, LLM, MLOps, and DevOps practices to ensure our solutions remain at the cutting edge. Troubleshoot and resolve complex technical issues across the cloud infrastructure Need Basis Technical skills required Level AWS Cloud Dev. - EC2, S3, Lambda, RDS, IAM, VPC, and CloudFormation

• Practitioner Machine learning frameworks
• TensorFlow, PyTorch, and Docker
• Practitioner DevOps
• Jenkins, GitLab CI, CircleCI, AWS CodePipeline,Terraform, CloudFormation
• Practitioner Docker and Kubernetes
• Practitioner MLOps tools (e.g., AWS SageMaker, TFX, MLflow)
• Practitioner AIOps services (e.g., AWS CloudWatch, Datadog)
• Practitioner